Food Science and Data Engineer - Pilgrim's Europe
Summary
A Knowledge Transfer Partnership graduate role embedded with Pilgrim's Europe (Moy Park) in Carrickfergus, developing an AI-enabled platform to optimise poultry processing settings, chill profile and pH control. The role is factory-based, combining on-site data gathering and monitoring with analytics work using tools like MATLAB, SPSS and SIMCA.
About the job:
Through the Knowledge Transfer Partnership (KTP) Programme, Moy Park Limited (Pilgrim's Europe) in partnership with Queen's University Belfast, have an exciting and unique employment opportunity for a dynamic and motivated Masters-level graduate to work on a project to develop an AI-enabled platform that optimises processing settings, chill profile and pH control across poultry operations; improving tenderness consistency, optimise yield, throughput and reducing complaints. This will support Pilgrim Europe's position as a trusted, high-quality, sustainable poultry processor. This is not a desk-based role. The successful candidate will spend a significant proportion of their time in the factory, gathering data and monitoring changes.
This role is company-based and will be delivered in collaboration with the Institute for Global Food Security (IGFS) at Queen's.
The successful candidate will become part of a team within Pilgrim's Europe (MoyPark Ltd). Pilgrim's is an industry-leading UK and European food company with over 40 facilities across the UK, Ireland, France and the Netherlands. The company's portfolio of brands includes Richmond, Fridge Raiders, Denny, Rollover, Oakhouse and Moy Park.
Information about the Company partner can be found at:
*** Please note that Queen's reserves the right to close the advert early once 80 applications have been received ***
About the person:
The successful candidate must have, and your application should clearly demonstrate that you meet the following criteria:
- Hold a Masters-level degree in a Food Science discipline, Mechanical Engineering, AI/Digitalisation/Data Analytics, or Statistics
- Relevant experience of using complex data analytics packages such as MATLAB, SPSS, SIMCA*
- Relevant experience of the evaluation of new technologies to include areas such as technology scoping, carrying out feasibility studies, and performance evaluation
- Relevant experience in sensor technologies
- Completion of a relevant research project or student placement in the agri-food sector
- Demonstrable knowledge and/or relevant experience of working with data and/or sensor technologies within the agri-food industry.
*may be demonstrated through the completion of a module, student project or placement.
Applicants must adequately evidence how they have gained relevant experience/knowledge/skills in detail, using examples and dates where appropriate to demonstrate that they meet these requirements. It is not sufficient to simply list duties/skills/modules/assignment titles as evidence.
Please note the above are not an exhaustive list. To be successful at shortlisting stage, please ensure you clearly evidence in your application how you meet the essential and, where applicable, desirable criteria listed in the Candidate Information document on our website.
WHJS1_NI